Required Datapoints
- Branded Search Volume (Current Period)
- Branded Search Volume (Previous Period)
- Time Frame: Weekly, monthly, or quarterly.
- Keyword Grouping: Branded terms.
Branded Search Volume Growth measures the percentage increase or decrease in branded search queries over a set period. It helps track brand momentum and marketing effectiveness over time.
Branded Search Volume Growth measures the rate at which users are increasingly (or decreasingly) searching for your brand by name, offering a trend-focused view of brand momentum, awareness gains, and campaign performance.
The relevance and interpretation of this metric shift depending on the model or product:
A rising growth rate indicates strong top-of-funnel traction. A decline may reveal fatigued campaigns, competitive overshadowing, or discoverability issues.
Segment by campaign, geography, or product line to identify which efforts are truly driving curiosity and name recognition.
Branded Search Volume Growth informs:
These are the main factors that directly impact the metric. Understanding these lets you know what levers you can pull to improve the outcome
Actionable ideas to optimize this KPI, from fast, low-effort wins to strategic initiatives that drive measurable impact.
Activities commonly tied to improving or operationalizing this KPI.
| Activity | Description |
|---|---|
| Trend Monitoring | Trend Monitoring involves the ongoing collection, evaluation, and interpretation of information about emerging trends, customer behaviors, competitor activities, and technological advancements within an industry. It turns signals into decisions, interventions, and measurable follow-up. Relevant KPIs include Branded Search Volume Growth. |
| Brand Growth Campaigns | Brand Growth Campaigns are strategic, cross-functional efforts aimed at increasing brand visibility, strengthening market positioning, and driving demand generation among target audiences. It coordinates execution across touchpoints so teams can move users or accounts toward the target outcome. Relevant KPIs include Branded Search Volume Growth. |
| Search Strategy | Search Strategy is a systematic process of identifying, prioritizing, and qualifying potential customer segments and accounts. It gives teams a clear plan for where to focus, how to sequence work, and what to measure. Relevant KPIs include Branded Search Volume Growth. |
| Share of Voice Analysis | Share of Voice Analysis focuses on Competitive Voice Benchmarking systematically measures and compares the frequency with which a company, its products, or key messages are referenced relative to competitors across relevant channels. It turns signals into decisions, interventions, and measurable follow-up. Relevant KPIs include Branded Search Volume Growth. |
This KPI is associated with the following stages in the AAARRR (Pirate Metrics) funnel:
This KPI is classified as a lagging Indicator. It reflects the results of past actions or behaviors and is used to validate performance or assess the impact of previous strategies.
This role is directly accountable for the KPI and is expected to drive progress and decisions around it.
These roles contribute directly to performance and typically partner on execution, reporting, or optimization.
These leading indicators influence this KPI and act as early signals that forecast future changes in this KPI.
These lagging indicators confirm, quantify, or amplify this KPI and help explain the broader business impact on this KPI after the fact.
How this KPI is structured in Cube.js, including its key measures, dimensions, and calculation logic for consistent reporting.
cube('BrandedSearchVolume', { sql: `SELECT * FROM branded_search_volume`,
measures: { brandedSearchVolumeCurrent: { sql: `branded_search_volume_current`, type: 'sum', title: 'Branded Search Volume (Current Period)', description: 'Total branded search volume for the current period.' },
brandedSearchVolumePrevious: { sql: `branded_search_volume_previous`, type: 'sum', title: 'Branded Search Volume (Previous Period)', description: 'Total branded search volume for the previous period.' },
brandedSearchVolumeGrowth: { sql: `100.0 * (branded_search_volume_current - branded_search_volume_previous) / NULLIF(branded_search_volume_previous, 0)`, type: 'number', title: 'Branded Search Volume Growth', description: 'Percentage growth in branded search volume from the previous period to the current period.' } },
dimensions: { id: { sql: `id`, type: 'number', primaryKey: true },
keywordGroup: { sql: `keyword_group`, type: 'string', title: 'Keyword Group', description: 'Grouping of branded terms.' },
timeFrame: { sql: `time_frame`, type: 'time', title: 'Time Frame', description: 'Time frame for the search volume data, such as weekly, monthly, or quarterly.' } }});Note: This is a reference implementation and should be used as a starting point. You’ll need to adapt it to match your own data model and schema